Discussion of paper ‘Revisiting Eurocode 8 formulae for periods of vibration and their employment in linear seismic analysis’ by Helen Crowley and Rui Pinho,Earthquake Engineering and Structural Dynamics 2010; 39(2):223–235     

S. Bahadir Yuksel 《地震工程与结构动力学》2011,40(11):1297-1298

  相似文献   

汶川Ms8.0地震灾害的非对称分布与成因分析          下载免费PDF全文

周庆  张春山  陈献程 《地震学报》2011,33(4):492-504

在汶川Ms8.0地震中,地震灾害在灾区相对于发震断层,呈现各种非对称分布.断层高角度逆冲诱发的崩塌、滑坡的规模与数量在断层上盘区远远高于断层下盘区,在垂直断层方向,高烈度区断层上盘宽度往往大于下盘宽度,上述不对称性反映了逆断层型地震存在加速度峰值的上盘效应;而在破裂的传播方向存在的地震波多普勒效应则造成沿长轴方向东北部...  相似文献   

汶川8.0级地震前后陇南地区地震宏观异常调查及分析          下载免费PDF全文

严武建  朱朝霞  李晓峰  张辉 《地震工程学报》2011,33(1):67-70,90

根据对2008年5月12日汶川8.0级大地震前后(2008年4月1日至7月13日)甘肃省陇南地区及甘南州舟曲县宏观异常的震后现场调查结果,经过资料整理分析和挑选可靠异常现象,对其时空分布特征进行了研究.结果表明,在时间上宏观异常的数量临近地震逐渐增多,在临震前形成峰值;在空间上宏观异常的分布在高烈度区较多.对宏观异常与震源机制关系以及宏观异常对地震预测可能发挥的作用等问题进行了讨论.  相似文献   

新疆乌苏5.1级地震前波速比异常震例研究   总被引：7，自引：0，他引：7  

龙海英  聂晓红  唐兰兰 《地震研究》2011,34(2):126-130

利用天山中段数字化地震波资料,采用多台和达法,计算2006年11月23日新疆乌苏5.1级地震前后波速比的变化情况,得到如下结果:(1)在空间分布上,乌苏5.1级地震前,波速比形成一个近似椭圆形低值异常区,且椭圆长半轴约为70 km,短半轴约为55 km,椭圆走向NW,地震就发生在该椭圆区域的西北部边缘;(2)在时间进程...  相似文献   

从欧洲抗震设计规范的一般规定浅谈结构抗震概念设计的重要性   总被引：1，自引：0，他引：1  

赵真  谢礼立 《地震工程与工程振动》2011,31(5):190-195

由于地震的作用以及在这种作用下的结构与构件的受力状况的复杂性和不确定性,结构抗震设计的计算假定与实际情况存在各种差异,甚至有时还根本无法计算.因此在这种情况下,为确保抗震结构性能,就不得不依赖结构抗震的概念设计.结构抗震概念设计是指工程师们根据结构地震破坏的形态和长期积累的实际工程经验等总结形成的符合工程师专业知识的基...  相似文献   

基于Landsat 8劈窗算法与混合光谱分解的城市热岛空间格局分析——以兰州市中心城区为例   总被引：3，自引：0，他引：3  

李瑶  潘竟虎 《干旱区地理》2015,38(1):111-119

在ENVI和GIS支持下,提出了基于Landsat 8遥感影像的地温反演劈窗算法,提取兰州市中心城区地表温度。利用FNEA和混合光谱分解法确定了兰州市中心城区的城市热岛中心、不透水面和植被盖度,分析了城市热岛空间分布格局以及地表温度与下垫面之间的关系。结果显示:基于Landsat 8数据地温反演的劈窗算法是可行的。兰州中心城区的高温区分布较集中,地表温度与植被呈较强的负相关,与不透水面呈不显著的正相关,与其他非光合物质呈正相关。  相似文献   

An approach of surface coal fire detection from ASTER and Landsat-8 thermal data: Jharia coal field,India     

《International Journal of Applied Earth Observation and Geoinformation》2015

Radiant temperature images from thermal remote sensing sensors are used to delineate surface coal fires, by deriving a cut-off temperature to separate coal-fire from non-fire pixels. Temperature contrast of coal fire and background elements (rocks and vegetation etc.) controls this cut-off temperature. This contrast varies across the coal field, as it is influenced by variability of associated rock types, proportion of vegetation cover and intensity of coal fires etc. We have delineated coal fires from background, based on separation in data clusters in maximum v/s mean radiant temperature (13th band of ASTER and 10th band of Landsat-8) scatter-plot, derived using randomly distributed homogeneous pixel-blocks (9 × 9 pixels for ASTER and 27 × 27 pixels for Landsat-8), covering the entire coal bearing geological formation. It is seen that, for both the datasets, overall temperature variability of background and fires can be addressed using this regional cut-off. However, the summer time ASTER data could not delineate fire pixels for one specific mine (Bhulanbararee) as opposed to the winter time Landsat-8 data. The contrast of radiant temperature of fire and background terrain elements, specific to this mine, is different from the regional contrast of fire and background, during summer. This is due to the higher solar heating of background rocky outcrops, thus, reducing their temperature contrast with fire. The specific cut-off temperature determined for this mine, to extract this fire, differs from the regional cut-off. This is derived by reducing the pixel-block size of the temperature data. It is seen that, summer-time ASTER image is useful for fire detection but required additional processing to determine a local threshold, along with the regional threshold to capture all the fires. However, the winter Landsat-8 data was better for fire detection with a regional threshold.  相似文献   

Mapping degraded grassland on the Eastern Tibetan Plateau with multi-temporal Landsat 8 data — where do the severely degraded areas occur?     

《International Journal of Applied Earth Observation and Geoinformation》2015

The Tibetan Plateau in Western China is the world’s largest alpine landscape, sheltering a rich diversity of native flora and fauna. In the past few decades, the Tibetan Plateau was found to suffer from grassland degradation processes. Grassland degradation is assumed to not only endanger biodiversity but also to increase the risk for natural hazards in other parts of the country which are ecologically and hydrologically connected to the area. However, the mechanisms behind the degradation processes remain poorly understood due to scarce baseline data and insufficient scientific research.We argue that remote sensing data can help to better understand degradation processes and patterns by: (1) identifying the distribution of severely degraded areas and (2) comparing the patterns of key spatial attributes of the identified areas (altitude above sea level, aspect, slope, administrative districts) with existing theories on degradation drivers. Therefore, we applied four Landsat 8 images covering large portions of the three counties Jigzhi, Baima and Darlag in the Eastern Tibetan Plateau. The dates of the Landsat scenes were selected to cover differing phenological stages of the ecosystem. Reference data were collected with a remotely piloted aircraft and a standard consumer RGB camera. To exploit the phenological information in the Landsat data as well as deal with the problem of cloud cover in multiple images, we developed a straightforward PCA-based procedure to merge the Landsat scenes. The merged Landsat data served as input to a supervised support vector machine classification which was validated with an iterative bootstrap procedure and an additional independent validation set. The considered classes were “high-cover grassland”, “grassland (including several stages of grassland vitality)”, “(severely) degraded grassland”, “green shrubland”, “grey shrubland”, “urban areas” and “water bodies”. Kappa accuracies ranged between 0.84 and 0.93 in the iterative procedure, while the independent validation led to a kappa accuracy of 0.76. Mean producer’s and user’s accuracies for all classes were higher than 80%, and confusion mainly occurred between the two shrubland classes and between the three grassland classes.Analysis of the slope, aspect and altitude values of the vegetation classes revealed that the degraded areas mostly occurred at the higher altitudes of the study area (4300–4600 m), with no strong connection to any specific slope or aspect. High-cover grassland was mostly located on sunny slopes at lower altitudes (less than 4300 m), while shrubland preferred shady, relatively steep slopes across all altitudes. These observations proved to be stable across the examined counties, while the proportions of land-cover classes differed between the examined regions. Most counties showed 5–7% severely degraded land cover. Darlag, the county located at the edge of the permafrost zone, and featuring the highest average altitude and lowest annual temperature and precipitation, was found to suffer from larger areas of severe degradation (14%).Therefore, our findings support a strong connection between degradation patterns and climatic as well as altitudinal gradients, with an increased degradation risk for high altitude areas and areas in colder and drier climatic zones. This is relevant information for pastoral management to avoid further degradation of high altitude pastures.  相似文献   

Landsat 8数据地表温度反演算法对比   总被引：12，自引：0，他引：12  

宋挺  段峥  刘军志  石浚哲  严飞  盛世杰  黄君  吴蔚 《遥感学报》2015,19(3):451-464

随着卫星遥感技术的发展,利用遥感反演地表温度的方法不断出现,如劈窗法、双角度法和单通道算法等。Landsat系列卫星的遥感数据是地表温度反演的重要数据之一。本文选择无锡周边区域为研究区,利用Landsat 8卫星遥感数据,对两种劈窗算法(Juan C.Jiménez-Muoz劈窗算法和Offer Rozenstein劈窗算法)和两种单窗算法(Juan C.Jiménez-Muoz单通道算法和覃志豪单窗算法)的地表温度反演精度进行了对比和敏感性分析。采用太湖16个浮标站的实测数据来验证了4种算法的反演精度。结果表明:两种劈窗算法的精度较高且较为接近,误差为0.7 K左右;覃志豪单窗算法和Juan C.Jiménez-Muoz单通道算法精度较低,误差分别为1.3 K和1.4 K左右。Juan C.Jiménez-Muoz劈窗算法对参数的敏感性最低,Juan C.Jiménez-Muoz单通道算法次之,覃志豪单窗算法和Offer Rozenstein劈窗算法敏感性相对最高。其中Juan C.Jiménez-Muoz单通道算法只适用于一定的水汽含量范围,有一定的局限性。  相似文献   

资源一号02C与Landsat8影像融合方法对比分析   总被引：1，自引：0，他引：1  

安萍  马世斌  张焜  王鹏  皮英楠 《测绘科学》2015,(11):57-62

针对以往关于资源一号02C和Landsat8卫星影像数据融合的研究不足的问题,该文利用前者在空间分辨率上高于后者、后者具有前者所不具有的光谱信息这一特性,选取主成分变换法、比值变换法、色彩变换法、高通滤波法和超分辨率贝叶斯法5种融合方法,分别对两种数据本身及数据间进行融合,并利用定性与定量的方法对融合结果进行评价,得出:资源一号02C星全色波段与多光谱波段数据融合结果中高通滤波法与超分辨率贝叶斯法效果较好,Landsat8OLI全色波段与多光谱数据融合结果中高通滤波法效果最好,资源一号02C星全色波段与Landsat8OLI多光谱数据融合结果中高通滤波法效果最好。  相似文献